Hi all,
This is a question only for knowledge purpose, I know someone introduced hybrid form of Dice and Cross Entropy to handle data imbalance problem in Colorectal Cancer Segmentation. Let me know about any recent loss function approach in ISLES, BRATS dataset?
Thanks
https://www.analyticsvidhya.com/blog/2017/03/imbalanced-classification-problem/
https://www.jeremyjordan.me/imbalanced-data/
Yuan, X., Xie, L., & Abouelenien, M. (2018). A regularized ensemble framework of deep learning for cancer detection from multi-class, imbalanced training data. Pattern Recognition, 77, 160-172.
Buda, M., Maki, A., & Mazurowski, M. A. (2018). A systematic study of the class imbalance problem in convolutional neural networks. Neural Networks, 106, 249-259.
Dear Saqib Qamar ,
In this paper " Joint Detection and Identification Feature Learning for Person Search ", the authors propose a loss function, referred to as Online Instance Matching (OIM) loss function, to handle the problem of imbalanced class in person recognition, see Section 3.2. By experiments, the proposed loss function is more suitable than common loss functions (e.g., Softmax).
Paper link: http://openaccess.thecvf.com/content_cvpr_2017/papers/Xiao_Joint_Detection_and_CVPR_2017_paper.pdf
GitHub link: https://github.com/ShuangLI59/person_search
I think this paper can help you.
https://www.analyticsvidhya.com/blog/2017/03/imbalanced-classification-problem/
https://www.jeremyjordan.me/imbalanced-data/
Yuan, X., Xie, L., & Abouelenien, M. (2018). A regularized ensemble framework of deep learning for cancer detection from multi-class, imbalanced training data. Pattern Recognition, 77, 160-172.
Buda, M., Maki, A., & Mazurowski, M. A. (2018). A systematic study of the class imbalance problem in convolutional neural networks. Neural Networks, 106, 249-259.
- Badges
- Science topic